Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Fuzzy Inference for Student Diagnosis in Adaptive Educational Hypermedia
SETN '02 Proceedings of the Second Hellenic Conference on AI: Methods and Applications of Artificial Intelligence
Neuro-fuzzy knowledge processing in intelligent learning environments for improved student diagnosis
Information Sciences—Informatics and Computer Science: An International Journal
Neuro Fuzzy Reasoner for Student Modeling
ICALT '06 Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies
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This paper presents the construction of a system suitable for student diagnosis with the use of neurofuzzy techniques. To be more specific, the extent of usefulness of Adaptive NeuroFuzzy Inference Systems (ANFIS) is examined for modeling automated evaluation of the answers and progress of deaf students' that possess basic knowledge of the English language and computer skills, within a virtual e-learning environment. The performance of the specific methods is evaluated with the correlation factor between the neural networks' response values and the real value data as well as the error between the neural networks' estimate values and the real value data during its training process and afterwards with unknown data that weren't used in the training process. The system was trained through data extracted from an educational project called ENFORA.